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Tools to visualize the results of a classification of cases. The graphical displays include stacked plots, silhouette plots, quasi residual plots, and class maps. Implements the techniques described and illustrated in Raymaekers, Rousseeuw and Hubert (2021), Class maps for visualizing classification results, Technometrics, appeared online. <doi:10.1080/00401706.2021.1927849> (open access) and Raymaekers and Rousseeuw (2021), Silhouettes and quasi residual plots for neural nets and tree-based classifiers, <doi:10.48550/arXiv.2106.08814>. Examples can be found in the vignettes: "Discriminant_analysis_examples","K_nearest_neighbors_examples", "Support_vector_machine_examples", "Rpart_examples", "Random_forest_examples", and "Neural_net_examples".
Version: | 1.2.3 |
Depends: | R (≥ 4.1.0) |
Imports: | stats, graphics, ggplot2, robustbase, e1071, cellWise, cluster, kernlab, gridExtra, rpart, randomForest |
Suggests: | knitr, reshape2, svd, rpart.plot, nnet, robCompositions |
Published: | 2023-04-23 |
DOI: | 10.32614/CRAN.package.classmap |
Author: | Jakob Raymaekers [aut, cre], Peter Rousseeuw [aut] |
Maintainer: | Jakob Raymaekers <jakob.raymaekers at kuleuven.be> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://doi.org/10.1080/00401706.2021.1927849, https://arxiv.org/abs/2106.08814 |
NeedsCompilation: | no |
CRAN checks: | classmap results |
Reference manual: | classmap.pdf |
Vignettes: |
Discriminant_analysis_examples K_nearest_neighbors_examples Neural_net_examples Random_forest_examples Rpart_examples Support_vector_machine_examples |
Package source: | classmap_1.2.3.tar.gz |
Windows binaries: | r-devel: classmap_1.2.3.zip, r-release: classmap_1.2.3.zip, r-oldrel: classmap_1.2.3.zip |
macOS binaries: | r-release (arm64): classmap_1.2.3.tgz, r-oldrel (arm64): classmap_1.2.3.tgz, r-release (x86_64): classmap_1.2.3.tgz, r-oldrel (x86_64): classmap_1.2.3.tgz |
Old sources: | classmap archive |
Please use the canonical form https://CRAN.R-project.org/package=classmap to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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